Search results for: word meaning retrieval
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 626

Search results for: word meaning retrieval

266 Development of Perez-Du Mortier Calibration Algorithm for Ground-Based Aerosol Optical Depth Measurement with Validation using SMARTS Model

Authors: Jedol Dayou, Jackson Hian Wui Chang, Rubena Yusoff, Ag. Sufiyan Abd. Hamid, Fauziah Sulaiman, Justin Sentian

Abstract:

Aerosols are small particles suspended in air that have wide varying spatial and temporal distributions. The concentration of aerosol in total columnar atmosphere is normally measured using aerosol optical depth (AOD). In long-term monitoring stations, accurate AOD retrieval is often difficult due to the lack of frequent calibration. To overcome this problem, a near-sea-level Langley calibration algorithm is developed using the combination of clear-sky detection model and statistical filter. It attempts to produce a dataset that consists of only homogenous and stable atmospheric condition for the Langley calibration purposes. In this paper, a radiance-based validation method is performed to further investigate the feasibility and consistency of the proposed algorithm at different location, day, and time. The algorithm is validated using SMARTS model based n DNI value. The overall results confirmed that the proposed calibration algorithm feasible and consistent for measurements taken at different sites and weather conditions.

Keywords: Aerosol optical depth, direct normal irradiance, Langley calibration, radiance-based validation, SMARTS.

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265 Secure and Efficient Transmission of Aggregated Data for Mobile Wireless Sensor Networks

Authors: A. Krishna Veni, R.Geetha

Abstract:

Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.

Keywords: Aggregation, lifetime, network security, wireless sensor network.

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264 Strategies for Development of Information Society in Montenegro

Authors: Vujica Lazovic, Tamara Djurickovic

Abstract:

Creation of information society, or in other words, a society based on knowledge, has wide consequences, both on individual and complete society, and in general – on a economy of one country. Development and implementation of ICT represents a stimulant for economic growth. On individual level, knowledge, skills and information gathered using ICT, are expanding individual possibilities of persons, enabling them to have access to timely sensitive information, such as market prices or investment conditions, possibilities to access Government-s or private development funds, etc. By doing so, productivity is increased both on individual and national level and therefore social wellbeing in general. In one word, creation of information society - a knowledge society is happening. This work will describe challenges and strategies that will follow the development as well as obstacles in creating information society – knowledge society in Montenegro.

Keywords: eDevelopment, eTransformation, informationsociety, knowledge economy

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263 Personal Information Classification Based on Deep Learning in Automatic Form Filling System

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: Personal information, deep learning, auto fill, NLP, document analysis.

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262 Eye Location Based on Structure Feature for Driver Fatigue Monitoring

Authors: Qiong Wang

Abstract:

One of the most important problems to solve is eye location for a driver fatigue monitoring system. This paper presents an efficient method to achieve fast and accurate eye location in grey level images obtained in the real-word driving conditions. The structure of eye region is used as a robust cue to find possible eye pairs. Candidates of eye pair at different scales are selected by finding regions which roughly match with the binary eye pair template. To obtain real one, all the eye pair candidates are then verified by using support vector machines. Finally, eyes are precisely located by using binary vertical projection and eye classifier in eye pair images. The proposed method is robust to deal with illumination changes, moderate rotations, glasses wearing and different eye states. Experimental results demonstrate its effectiveness.

Keywords: eye location, structure feature, driver fatiguemonitoring

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261 Impact of Electronic Guest Relationship Management (e-GRM) on Brand Loyalty: The Case of Croatian Hotels

Authors: Marina Laškarin, Vlado Galičić

Abstract:

Quick adoption of e-business and emerging influence of “Electronic Word of Mouth e-WOM” communication on guests made leading hotel brands successful examples of electronic guest relationship management. Main reasons behind such success are well established procedures in collection, analysis and usage of highly valuable data available on the Internet, generated through some form of e-GRM programme. E-GRM is more than just a technology solution. It’s a system which balance respective guest demands, hotel technological capabilities and organizational culture of employees, discharging the universal approach in guest relations “same for all”. The purpose of this research derives from the necessity of determining the importance of monitoring and applying e-WOM communication as one of the methods used in managing guest relations. This paper analyses and compares different hotelier’s opinions on e-WOM communication.

Keywords: Brand loyalty, e-WOM communication, GRM programmes.

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260 In Search of the Meaning of Entrepreneurship

Authors: H. Fabian Weber, Betina Szkudlarek

Abstract:

The following study aims to outline, whether the perceptions of entrepreneurs about their entrepreneurial activities and the underlying meanings of their activities are universal or whether they vary systematically across cultures. In contrast to previous studies, the phenomenographical approach and the resulting findings of this study provide new insights into what constitutes entrepreneurship by drawing an inference from the perceptions of entrepreneurs in the United States and in Germany. Culture is shown to have an important impact on entrepreneurship, since the underlying meanings of entrepreneurship vary significantly among the two sample groups. Furthermore, the study sheds more light on the culturally contingent 'why' of entrepreneurship by looking at the internal motivations of individuals instead of exclusively focusing on character traits or external influences of the respective economic environments.

Keywords: Cross-Cultural Management, Entrepreneurship, Phenomenography, Qualitative Research.

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259 Bangla Vowel Characterization Based on Analysis by Synthesis

Authors: Syed Akhter Hossain, M. Lutfar Rahman, Farruk Ahmed

Abstract:

Bangla Vowel characterization determines the spectral properties of Bangla vowels for efficient synthesis as well as recognition of Bangla vowels. In this paper, Bangla vowels in isolated word have been analyzed based on speech production model within the framework of Analysis-by-Synthesis. This has led to the extraction of spectral parameters for the production model in order to produce different Bangla vowel sounds. The real and synthetic spectra are compared and a weighted square error has been computed along with the error in the formant bandwidths for efficient representation of Bangla vowels. The extracted features produced good representation of targeted Bangla vowel. Such a representation also plays essential role in low bit rate speech coding and vocoders.

Keywords: Speech, vowel, formant, synthesis, spectrum, LPC.

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258 Self-Assembling Hypernetworks for Cognitive Learning of Linguistic Memory

Authors: Byoung-Tak Zhang, Chan-Hoon Park

Abstract:

Hypernetworks are a generalized graph structure representing higher-order interactions between variables. We present a method for self-organizing hypernetworks to learn an associative memory of sentences and to recall the sentences from this memory. This learning method is inspired by the “mental chemistry" model of cognition and the “molecular self-assembly" technology in biochemistry. Simulation experiments are performed on a corpus of natural-language dialogues of approximately 300K sentences collected from TV drama captions. We report on the sentence completion performance as a function of the order of word-interaction and the size of the learning corpus, and discuss the plausibility of this architecture as a cognitive model of language learning and memory.

Keywords: Linguistic recall memory, sentence completion task, self-organizing hypernetworks, cognitive learning and memory.

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257 Learning Styles of University Students in Bangkok: The Characteristics and the Relevant Instructional Context

Authors: Chaiwat Tantarangsee

Abstract:

The purposes of this study are 1) to identify learning styles of university students in Bangkok, and 2) to study the frequency of the relevant instructional context of the identified learning styles. Learning Styles employed in this study are those of Honey and Mumford, which include 1) Reflectors, 2) Theorists, 3) Pragmatists, and 4) Activists. The population comprises 1383 students and 5 lecturers. Research tools are 2 questionnaires – one used for identifying students- learning styles, and the other used for identifying the frequency of the relevant instructional context of the identified learning styles. The research findings reveal that 32.30 percent - are Activists, while 28.10 percent are Theorists, 20.10 are Reflectors, and 19.50 are Pragmatists. In terms of the relevant instructional context of the identified 4 learning styles, it is found that the frequency level of the instructional context is totally in high level. Moreover, 2 lists of the context being conducted most frequently are 'Lead'in activity to review background knowledge,- and 'Information retrieval report.' And these two activities serve the learning styles of theorists and activists. It is, therefore, suggested that more instructional context supporting the activists, the majority of the population, learning best by doing, as well as emotional learning situation should be added.

Keywords: Instructional Context, Learning Styles, Learning Style Preference, and Learning Style Questionnaire.

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256 Logistic Model Tree and Expectation-Maximization for Pollen Recognition and Grouping

Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

Abstract:

Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: Pollen recognition, logistic model tree, expectation-maximization, local binary pattern.

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255 A Novel Nano-Scaled SRAM Cell

Authors: Arash Azizi Mazreah, Mohammad Reza Sahebi, Mohammad T. Manzuri Shalmani

Abstract:

To help overcome limits to the density of conventional SRAMs and leakage current of SRAM cell in nanoscaled CMOS technology, we have developed a four-transistor SRAM cell. The newly developed CMOS four-transistor SRAM cell uses one word-line and one bit-line during read/write operation. This cell retains its data with leakage current and positive feedback without refresh cycle. The new cell size is 19% smaller than a conventional six-transistor cell using same design rules. Also the leakage current of new cell is 60% smaller than a conventional sixtransistor SRAM cell. Simulation result in 65nm CMOS technology shows new cell has correct operation during read/write operation and idle mode.

Keywords: SRAM Cell, leakage current, cell area.

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254 Puhr(i)puhr ‘Son’s Son’ at the Shahpuhr Inscription at Haji-Abad

Authors: Behzad Moeini Sam, Sara Mohammadi Avandi, Abbas Moradi Zirkuhi

Abstract:

Ancient Near East civilizations were successive powers with a similar structure as the Median and Persian Empires that came after them; that is, the ancient Empires were founded under new leadership, and their political power transferred from one nation to another. The replacement of the Iranians instead of the Mesopotamian civilizations caused the Old Iranian languages to influence the Mesopotamian ones. However, the changes were relatively small. This paper aims to compare the word of puhre(ī)puhr or son’s son in Haji-Abad inscription with that of the son of the son in Mesopotamian texts to find out the relationship with the Mesopotamian languages. First, we introduced the morphological derivation of ‘Grandchild’ from the Indo-European to the New Persian language; second, we searched for the same in the Mesopotamian languages from Sumerian to the Neo-Babylonian Period. Thus, we conclude that it is logical to assume puhre(ī)puhr’s (son’s son) morphology at the Haji-Abad inscription may be affected by that of the Mesopotamian languages.

Keywords: Indo-European, Mesopotamia, puhre(ī)puhr, son’s son.

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253 Developing a Coronavirus Academic Paper Sorting Application

Authors: Christina A. van Hal, Xiaoqian Jiang, Luyao Chen, Yan Chu, Robert D. Jolly, Yaobin Lin, Jitian Zhao, Kang Lin Hsieh

Abstract:

The COVID-19 Literature Summary App, now live on the university website, was created for the primary purpose of enabling academicians and clinicians to quickly sort through the vast array of recent coronavirus publications by topics of interest. Multiple methods of summarizing and sorting the manuscripts were created. A summary page introduces the application function and capabilities, while an interactive map provides daily updates on infection, death, and recovery rates. A page with a pivot table allows publication sorting by topic, with an interactive data table that allows sorting topics by columns, as wells as the capability to view abstracts. Additionally, publications may be sorted by the medical topics they cover. We used the CORD-19 database to compile lists of publications. The data table can sort binary variables, allowing the user to pick desired publication topics, such as papers that describe COVID-19 symptoms. The application is primarily designed for use by researchers but can be used by anybody who wants a faster and more efficient means of locating papers of interest. 

Keywords: COVID-19, literature summary, information retrieval, snorkel

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252 MIBiClus: Mutual Information based Biclustering Algorithm

Authors: Neelima Gupta, Seema Aggarwal

Abstract:

Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.

Keywords: Biclustering, mutual information.

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251 Impovement of a Label Extraction Method for a Risk Search System

Authors: Shigeaki Sakurai, Ryohei Orihara

Abstract:

This paper proposes an improvement method of classification efficiency in a classification model. The model is used in a risk search system and extracts specific labels from articles posted at bulletin board sites. The system can analyze the important discussions composed of the articles. The improvement method introduces ensemble learning methods that use multiple classification models. Also, it introduces expressions related to the specific labels into generation of word vectors. The paper applies the improvement method to articles collected from three bulletin board sites selected by users and verifies the effectiveness of the improvement method.

Keywords: Text mining, Risk search system, Corporate reputation, Bulletin board site, Ensemble learning

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250 Research on Strategy for Automated Scaleless-Map Compilation

Authors: Yin Jie, Qin Qiming, Yin Yong

Abstract:

As a tool for human spatial cognition and thinking, the map has been playing an important role. Maps are perhaps as fundamental to society as language and the written word. Economic and social development requires extensive and in-depth understanding of their own living environment, from the scope of the overall global to urban housing. This has brought unprecedented opportunities and challenges for traditional cartography . This paper first proposed the concept of scaleless-map and its basic characteristics, through the analysis of the existing multi-scale representation techniques. Then some strategies are presented for automated mapping compilation. Taking into account the demand of automated map compilation, detailed proposed the software - WJ workstation must have four technical features, which are generalization operators, symbol primitives, dynamically annotation and mapping process template. This paper provides a more systematic new idea and solution to improve the intelligence and automation of the scaleless cartography.

Keywords: scaleless-map, strategy, map generalization, automated compilation, WJ workstation.

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249 Support Vector Machine based Intelligent Watermark Decoding for Anticipated Attack

Authors: Syed Fahad Tahir, Asifullah Khan, Abdul Majid, Anwar M. Mirza

Abstract:

In this paper, we present an innovative scheme of blindly extracting message bits from an image distorted by an attack. Support Vector Machine (SVM) is used to nonlinearly classify the bits of the embedded message. Traditionally, a hard decoder is used with the assumption that the underlying modeling of the Discrete Cosine Transform (DCT) coefficients does not appreciably change. In case of an attack, the distribution of the image coefficients is heavily altered. The distribution of the sufficient statistics at the receiving end corresponding to the antipodal signals overlap and a simple hard decoder fails to classify them properly. We are considering message retrieval of antipodal signal as a binary classification problem. Machine learning techniques like SVM is used to retrieve the message, when certain specific class of attacks is most probable. In order to validate SVM based decoding scheme, we have taken Gaussian noise as a test case. We generate a data set using 125 images and 25 different keys. Polynomial kernel of SVM has achieved 100 percent accuracy on test data.

Keywords: Bit Correct Ratio (BCR), Grid Search, Intelligent Decoding, Jackknife Technique, Support Vector Machine (SVM), Watermarking.

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248 Hybrid Modeling Algorithm for Continuous Tamil Speech Recognition

Authors: M. Kalamani, S. Valarmathy, M. Krishnamoorthi

Abstract:

In this paper, Fuzzy C-Means clustering with Expectation Maximization-Gaussian Mixture Model based hybrid modeling algorithm is proposed for Continuous Tamil Speech Recognition. The speech sentences from various speakers are used for training and testing phase and objective measures are between the proposed and existing Continuous Speech Recognition algorithms. From the simulated results, it is observed that the proposed algorithm improves the recognition accuracy and F-measure up to 3% as compared to that of the existing algorithms for the speech signal from various speakers. In addition, it reduces the Word Error Rate, Error Rate and Error up to 4% as compared to that of the existing algorithms. In all aspects, the proposed hybrid modeling for Tamil speech recognition provides the significant improvements for speechto- text conversion in various applications.

Keywords: Speech Segmentation, Feature Extraction, Clustering, HMM, EM-GMM, CSR.

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247 The Destruction of Confucianism and Socialism in Chinese Popular Comedy Films

Authors: Shu Hui

Abstract:

Since 2010, the genre of comedy became predominant in film market in China. However, compared with the huge commercial success, these films received severe public criticism. These films are referred as trash (lan pian) by the public because of the fragment narrative, the non-professional photographing and advocating money warship. The paper aims to explain the contradictive phenomena between the higher box office and the lower mouth of word within hegemony theory. Four popular comedies that ranked top 20 in domestic revenue in the year the film released will be chosen to analyze their popularity in general. Differing from other popular films, these comedies’ popularity is generated from their disruptive pleasures instead of good stories or photographing. The destruction in Confucianism and socialism formulated the public consent or popularity, and caused the public criticism as well. Moreover, the happy-endings restore the normality at the superficial level.

Keywords: Confucianism, destruction, reconciliation, socialism.

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246 Knowledge Management and Tourism: An Exploratory Study Applied to Travel Agents in Egypt

Authors: Mohammad Soliman, Mohamed A. Abou-Shouk

Abstract:

Knowledge management focuses on the development, storage, retrieval, and dissemination of information and expertise. It has become an important tool to improve performance in tourism enterprises. This includes improving decision-making, developing customer services, and increasing sales and profits. Knowledge management adoption depends on human, organizational and technological factors. This study aims to explore the concept of knowledge management in travel agents in Egypt. It explores the requirements of adoption and its impact on performance in these agencies. The study targets Category A travel agents in Egypt. The population of the study encompasses Category A travel agents having online presence. An online questionnaire is used to collect data from managers of travel agents. This study is useful for travel agents who are in urgent need to restructure their intermediary role and support their survival in the global travel market. The study sheds light on the requirements of adoption and the expected impact on performance. This could help travel agents identify their situation and the determine the extent to which they are ready to adopt knowledge management. This study is contributing to knowledge by providing insights from the tourism sector in a developing country where the concept of knowledge management is still in its infancy stages.

Keywords: Benefits, determinants, Egypt, knowledge management, travel agents.

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245 SBTAR: An Enhancing Method for Automate Test Tools

Authors: Noppakit Nawalikit, Pattarasinee Bhattarakosol

Abstract:

Since Software testing becomes an important part of Software development in order to improve the quality of software, many automation tools are created to help testing functionality of software. There are a few issues about usability of these tools, one is that the result log which is generated from tools contains useless information that the tester cannot use result log to communicate efficiently, or the result log needs to use a specific application to open. This paper introduces a new method, SBTAR that improves usability of automated test tools in a part of a result log. The practice will use the capability of tools named as IBM Rational Robot to create a customized function, the function would generate new format of a result log which contains useful information faster and easier to understand than using the original result log which was generated from the tools. This result log also increases flexibility by Microsoft Word or WordPad to make them readable.

Keywords: Software Automation Testing, Automated test tool, IBM Rational Robot.

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244 Clustering Categorical Data Using the K-Means Algorithm and the Attribute’s Relative Frequency

Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

Abstract:

Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.

Keywords: Clustering, k-means, categorical datasets, pattern recognition, unsupervised learning, knowledge discovery.

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243 Using the Geographic Information System (GIS) in the Sustainable Transportation

Authors: Zahra Gharineiat, Malik Khalfan

Abstract:

The significance of emissions from the road transport sector (such as air pollution, noise, etc) has grown considerably in recent years. In Australia, 14.3% of national greenhouse gas emissions in 2000 were the transport sector-s share which 12.9% of net national emissions were related to a road transport alone. Considering the growing attention to the green house gas(GHG) emissions, this paper attempts to provide air pollution modeling aspects of environmental consequences of the road transport by using one of the best computer based tools including the Geographic Information System (GIS). In other word, in this study, GIS and its applications is explained, models which are used to model air pollution and GHG emissions from vehicles are described and GIS is applied in real case study that attempts to forecast GHG emission from people who travel to work by car in 2031 in Melbourne for analysing results as thematic maps.

Keywords: Geographic Information System (GIS), Green HouseGas(GHG) emission, sustainable development, transportation

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242 Parallel Text Processing: Alignment of Indonesian to Javanese Language

Authors: Aji P. Wibawa, Andrew Nafalski, Neil Murray, Wayan F. Mahmudy

Abstract:

Parallel text alignment is proposed as a way of aligning bahasa Indonesia to words in Javanese. Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).

Keywords: Parallel text alignment, phrase pair combination, edit distance coefficient, Javanese-Indonesian language.

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241 Taking People, Process and Partnership on Board for Participatory Decision Making

Authors: B. Mikulskienė

Abstract:

Public administration institutions in cooperation with politicians are not the sole policy decision makers in full meaning any longer. Meanwhile, a special role, namely steering the decision making process, could be delegated to them. Despite the wide scientific discussion on different aspects what has direct impact on policy creation, there is a lack of holistic practical managerial advice, which could integrate infrastructure of policy decision making with intellectual capital and with interconnection of partnership. The proposed harmonized decision making model of process, people and partnership entitled by acronym HM-3P is analyzed as a framework for implementation of public administration steering role seeking the coherent social involvement in policy decision making.

Keywords: participatory decision making, partnership, stakeholders.

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240 A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: Active Contour, Bayesian, Echocardiographic image, Feature vector.

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239 Development of Fuzzy Logic Control Ontology for E-Learning

Authors: Muhammad Sollehhuddin A. Jalil, Mohd Ibrahim Shapiai, Rubiyah Yusof

Abstract:

Nowadays, ontology is common in many areas like artificial intelligence, bioinformatics, e-commerce, education and many more. Ontology is one of the focus areas in the field of Information Retrieval. The purpose of an ontology is to describe a conceptual representation of concepts and their relationships within a particular domain. In other words, ontology provides a common vocabulary for anyone who needs to share information in the domain. There are several ontology domains in various fields including engineering and non-engineering knowledge. However, there are only a few available ontology for engineering knowledge. Fuzzy logic as engineering knowledge is still not available as ontology domain. In general, fuzzy logic requires step-by-step guidelines and instructions of lab experiments. In this study, we presented domain ontology for Fuzzy Logic Control (FLC) knowledge. We give Table of Content (ToC) with middle strategy based on the Uschold and King method to develop FLC ontology. The proposed framework is developed using Protégé as the ontology tool. The Protégé’s ontology reasoner, known as the Pellet reasoner is then used to validate the presented framework. The presented framework offers better performance based on consistency and classification parameter index. In general, this ontology can provide a platform to anyone who needs to understand FLC knowledge.

Keywords: Engineering knowledge, fuzzy logic control ontology, ontology development, table of contents.

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238 The Impact of Dialectal Differences on the Perception of Japanese Gemination: A Case Study of Cantonese Learners

Authors: Honghao Ren, Mariko Kondo

Abstract:

This study investigates the perceptual features of Japanese obstruent geminates among Chinese learners of Japanese, focusing on the dialectal effect of the checked-tone, a syllable that ends in a stop consonant or a glottal stop, which is similar to Japanese obstruent geminates phonetically. In this study, 41 native speakers of Cantonese are divided into two groups based on their proficiency as well as learning period of Japanese. All stimuli employed in this study are made into C[p,k,s]+V[a,e,i] structure such as /apa/, /eke/, /isi/. Both original sounds and synthesized sounds are used in three different parts of this study. The results of the present study show that the checked-tone does have the positive effect on the perception of Japanese gemination. Furthermore, the proportion of closure duration in the entire word would be a more reliable and appropriate criterion in testing this kind of task.

Keywords: Dialectal differences, Cantonese learners of Japanese, acoustic experiment, closure duration.

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237 The Effectiveness of Therapeutic Exercise on Motor Skills and Attention of Male Students with Autism Spectrum Disorder

Authors: Masoume Pourmohamadreza-Tajrishi, Parviz Azadfallah

Abstract:

Autism spectrum disorders (ASD) involve myriad aberrant perceptual, cognitive, linguistic, and social behaviors. The term spectrum emphasizes that the disabilities associated with ASD fall on a continuum from relatively mild to severe. People with ASD may display stereotyped behaviors such as twirling, spinning objects, flapping the hands, and rocking. The individuals with ASD exhibit communication problems due to repetitive/restricted behaviors. Children with ASD who lack the motivation to learn, who do not enjoy physical challenges, or whose sensory perception results in confusing or unpleasant feedback from movement may not become sufficiently motivated to practice motor activities. As a result, they may show both a delay in developing certain motor skills. Additionally, attention is an important component of learning. As far as children with ASD have problems in joint attention, many education-based programs are needed to consider some aspects of attention and motor activities development for students with ASD. These programs focus on the basic movement skills that are crucial for the future development of the more complex skills needed in games, dance, sports, gymnastics, active play, and recreational physical activities. The purpose of the present research was to determine the effectiveness of therapeutic exercise on motor skills and attention of male students with ASD. This was an experimental study with a control group. The population consisted of 8-10 year-old male students with ASD and 30 subjects were selected randomly from an available center suitable for the children with ASD. They were evaluated by the Basic Motor Ability Test (BMAT) and Persian version of computerized Stroop color-word test and randomly assigned to an experimental and control group (15 students in per group). The experimental group participated in 16 therapeutic exercise sessions and received therapeutic exercise program (twice a week; each lasting for 45 minutes) designed based on the Spark motor program while the control group did not. All subjects were evaluated by BMAT and Stroop color-word test after the last session again. The collected data were analyzed by using multivariate analysis of covariance (MANCOVA). The results of MANCOVA showed that experimental and control groups had a significant difference in motor skills and at least one of the components of attention (correct responses, incorrect responses, no responses, the reaction time of congruent words and reaction time of incongruent words in the Stroop test). The findings showed that the therapeutic exercise had a significant effect on motor skills and all components of attention in students with ASD. We can conclude that the therapeutic exercise led to promote the motor skills and attention of students with ASD, so it is necessary to design or plan such programs for ASD students to prevent their communication or academic problems.

Keywords: Attention, autism spectrum disorder, motor skills, therapeutic exercise.

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